A fast implementation of Random Forests, particularly suited for high dimensional data. Ensembles of classification, regression, survival and probability prediction trees are supported. Data from genome-wide association studies can be analyzed efficiently. In addition to data frames, datasets of class 'gwaa.data' (R package 'GenABEL') can be directly analyzed.
| Version: | 0.5.0 |
| Depends: | R (≥ 3.1) |
| Imports: | Rcpp (≥ 0.11.2) |
| LinkingTo: | Rcpp |
| Suggests: | survival, testthat, GenABEL |
| Published: | 2016-06-24 |
| Author: | Marvin N. Wright |
| Maintainer: | Marvin N. Wright <wright at imbs.uni-luebeck.de> |
| BugReports: | https://github.com/imbs-hl/ranger/issues |
| License: | GPL-3 |
| URL: | https://github.com/imbs-hl/ranger |
| NeedsCompilation: | yes |
| Materials: | NEWS |
| In views: | MachineLearning |
| CRAN checks: | ranger results |
| Reference manual: | ranger.pdf |
| Package source: | ranger_0.5.0.tar.gz |
| Windows binaries: | r-devel: ranger_0.5.0.zip, r-release: ranger_0.5.0.zip, r-oldrel: ranger_0.5.0.zip |
| OS X Mavericks binaries: | r-release: ranger_0.5.0.tgz, r-oldrel: ranger_0.5.0.tgz |
| Old sources: | ranger archive |
| Reverse depends: | Boruta |
| Reverse suggests: | GSIF, mlr, purge |